1. Field of Invention
The present invention relates to the field of digital communications. More specifically, the present invention provides a method and apparatus to reduce the signal-to-noise ratio of a communication system and a method for data rate optimization in a multicarrier modulation framework.
2. Background of Invention
Modern communication systems involve complex modulation and transmission schemes. To achieve superior performance, systems have to be robust against noise and distortion as they are the prime limiting factors. Therefore, noise reduction and compensation for channel distortion have been of principle interest. Primarily, noise reduction can provide significant performance enhancement in applications including, but not limited to, wired and wireless communications, image processing and speech processing.
Removal or suppression of noise can be accomplished using several different approaches. One of the common approaches is data averaging. As is known in the art of data averaging, a signal is transmitted repeatedly over time. The data is received at the receiver periodically. While propagating through the transmission medium, the signal is corrupted by noise. Theoretically, the corrupting noise is random and its effects can be eliminated through averaging the signal over all repetitions. This corruptive random noise, commonly referred to as Additive White Gaussian Noise (AWGN), is well known in the art as a means of modeling noise in communication system analysis. In the presence of AWGN it is known in the art to substantially improve the signal quality through averaging. The averaging approach can also be helpful in the detection of information in extremely noisy environments. While deploying the noise averaging technique, a trade-off should be made between the number of repetitions and the amount of noise-reduction or signal-to-noise ratio (SNR) improvement.
In a typical information transmission system where the information sent out may be in the form of data, speech, or video, an efficient mechanism is required to segregate the signal and the noise. Moreover, to improve the link quality, it is often necessary to train the receiver before actual data transmission begins. In such cases, usage of noise reduction algorithms helps further to enhance the system performance by converging equalizer weights, providing faster convergence, enabling improved channel estimation and improved timing extraction.
In a communication system known in the art, the signal is modulated at the transmitter through a pre-determined modulation scheme, and is transmitted over a medium. The signal may be up-converted to RF frequency using a high frequency carrier signal. While propagating through the medium, the transmitted signal is distorted and is subjected to interferences. The receiver receives the signal at an antenna or front-end. The received signal then may undergo some frequency down-conversion and amplification before it is converted back to the baseband. Then, the majority of signal processing and detection is accomplished to extract the information. At this point, the receiver may also use de-noising or noise-reduction algorithms to improve the signal quality or SNR. After this pre-detection processing is completed, the transmitted information is deciphered by the detection stages.
While de-noising methods are known in the art, what is needed in the art is a method and apparatus addressing the issue of signal-to-noise ratio that provides a greater noise reduction of the received signal over the noise reduction algorithms known in the art.